Usability features for integrated insulin delivery system

ABSTRACT

Various systems and methods for improving the usability of continuous glucose monitors and drug delivery pumps are described.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.61/180,649, filed May 22, 2009, which is incorporated herein byreference in its entirety.

This application is also related to U.S. application Ser. No. ______entitled “Methods For Reducing False Hypoglycemia Alarm Occurrence,”(U.S. Provisional No. 61/180,700, filed May 22, 2009); U.S. applicationSer. No. ______ entitled “Safety Features For Integrated InsulinDelivery System,” (U.S. Provisional Application No. 61/180,627, filedMay 22, 2009); U.S. application Ser. No. ______ entitled “Safety LayerFor Integrated Insulin Delivery System,” (U.S. Provisional ApplicationNo. 61/180,774, filed May 22, 2009); and U.S. application Ser. No.______ entitled “Adaptive Insulin Delivery System,” (U.S. ProvisionalApplication No. 61/180,767, filed May 22, 2009).

BACKGROUND

Diabetes is a metabolic disorder that afflicts tens of millions ofpeople throughout the world. Diabetes results from the inability of thebody to properly utilize and metabolize carbohydrates, particularlyglucose. Normally, the finely tuned balance between glucose in the bloodand glucose in bodily tissue cells is maintained by insulin, a hormoneproduced by the pancreas which controls, among other things, thetransfer of glucose from blood into body tissue cells. Upsetting thisbalance causes many complications and pathologies including heartdisease, coronary and peripheral artery sclerosis, peripheralneuropathies, retinal damage, cataracts, hypertension, coma, and deathfrom hypoglycemic shock.

In persons with insulin-dependent diabetes, the symptoms of the diseasecan be controlled by administering additional insulin (or other agentsthat have similar effects) by injection or by external or implantableinsulin pumps. The “correct” insulin dosage is a function of the levelof glucose in the blood. Ideally, insulin administration should becontinuously readjusted in response to changes in glucose level.

Presently, systems are available for continuously monitoring a person'sglucose levels by implanting a glucose sensitive probe into the person.Such probes measure various properties of blood or other tissues,including optical absorption, electrochemical potential and enzymaticproducts. The output of such sensors can be communicated to a hand helddevice or controller that is used to calculate an appropriate dosage ofinsulin to be delivered to the user of the continuous glucose monitor(CGM) in view of several factors, such as the user's present glucoselevel, insulin usage rate, carbohydrates consumed or to be consumed andexercise, among others. These calculations can then be used to control apump that delivers the insulin, either at a controlled “basal” rate, oras a “bolus” into the user. When provided as an integrated system, thecontinuous glucose monitor, controller and pump work together to providecontinuous glucose monitoring and insulin pump control.

Such systems can be closed loop systems, where the amount of insulinbeing delivered is completely controlled by the controller and pump inconjunction with glucose level data received from the CGM device.Alternatively, such systems may be open loop systems, where the userevaluates the glucose level information from a glucose monitoring deviceand then instructs the pump accordingly, or the system may be asemi-closed loop system that combines various aspects of a closed loopand open loop system.

Typically, present systems may be considered to be open or semi-closedloop in that they require intervention by a user to calculate andcontrol the amount of insulin to be delivered. However, there may beperiods when the user is not able to adjust insulin delivery. Forexample, when the user is sleeping, he or she cannot intervene in thedelivery of insulin, yet control of a patient's glucose level is stillnecessary. A system capable of integrating and automating the functionsof glucose monitoring and controlled insulin delivery into a closed loopsystem would be useful in assisting users in maintaining their glucoselevels, especially during periods of the day when they are unable orunwilling to the required calculations to adjust insulin deliver tocontrol their glucose level.

What has been needed, and heretofore unavailable, is an integrated,automated system combining continuous glucose monitoring and controlledinsulin delivery. Such a system would include various features to insurethe accuracy of the glucose monitor and to protect the user from eitherunder- or over-dosage of insulin. The system would include variousfunctions for improving the usability, control, and safety of thesystem, including a variety of alarms which could be set by a user or atechnician to avoid false alarms while ensuring adequate sensitivity toprotect the user. The present invention satisfies these and other needs.

SUMMARY OF THE INVENTION

Briefly, and in general terms, the invention is directed to new andimproved systems and methods for management of a user's glucose level,including systems and methods for improving the usability and safety ofsuch systems including continuous glucose monitors and a drug deliverypumps.

In one aspect, the invention is directed to a system and method for usewhen insulin delivery is to be restarted after an unexpected stop indelivery. In this aspect of the invention, insulin history and glucoselevel history are used for calculating and recommending a bolus volumeof insulin to be delivered to bring a user's insulin on board, that is,residual insulin that is unmetabolised and circulating in the user'sblood stream since insulin was last added, up to the level it would havebeen had insulin delivery not been stopped.

In another aspect, a safe amount and duration of basal rate insulindelivery is determined using model-based calculation of insulin onboard, past insulin delivery information, past and present glucoseinformation of the user and a predicted glucose profile over anear-future time horizon, among other factors, in the event that aclosed loop insulin delivery system terminates closed loop operationunexpectedly.

In still another aspect, the invention includes a system and method forenhancing alarm avoidance with pre-emptive pump control commandmodification, which is advantageous when compared with simply muting analarm, and is less annoying than a persistent projected low glucosealarm. In yet another aspect, a user interface is provided thatintegrates and cooperates with the enhanced alarm avoidance system andmethod to facilitate use of the system.

In a further aspect, a system and method is included that is directed toreducing the frequency of false low glucose alarms, particularly when aninsulin delivery system is operating in a closed loop mode, by allowingfor the possibility of the complete or partial recovery from anartifact, such as a sensor drop out, to occur prior to an alarmpresentation to a user of the system.

In another aspect, a model-based calculation of the present andnear-future values of best estimate and upper/lower bounds of glucose ismade to adjust a tiered alarm mechanism in order to account forpredicted hypoglycemic and hyperglycemic events.

In yet another aspect, the invention includes a method for determining abolus volume to be administered to make up for a cessation of basaldelivery of insulin, comprising: determining an amount of insulinremaining in a user's body such that insulin remaining=amount of insulindelivered before cessation×(user's insulin action time minus the timesince insulin was last delivered)/(user's insulin action time); andcalculating a bolus delivery to equal the amount of basal delivery lost.In another aspect, determining an amount of insulin remaining includesusing a model to estimate the amount of insulin remaining.

In still another aspect, the invention includes a method of determiningan insulin delivery rate when a closed loop insulin delivery systemterminates unexpectedly, comprising: a) providing a glucose level andpredicting a future glucose level in order to determine the appropriateinsulin bolus for the latest control action, and assuming that thiscommanded is immediately followed by open loop control where thepre-programmed basal delivery amount will be in effect thereafter; b)analyzing the future glucose level using this latest bolus value plus afuture basal rate to determine if the future glucose level isacceptable, and if so, waiting for a selected period of time andrepeating a); c) if the glucose level of b) is not acceptable, computingan alternate maximum temporary basal delivery amount that is lower thanthe previously assumed basal rate, such that the predicted futureglucose level is acceptable, and if so, providing a temporary basalcommand at the computed basal rate and duration, and predicting a futureglucose level; and if so, waiting for a selected period of time andrepeating a); d) if the predicted future glucose level is unacceptable,projecting a future glucose level using the lowest temporary basaldelivery rate computable in step c) and a maximum duration that isshorter than the maximum delivery duration, and, if the future glucoselevel is acceptable, providing a temporary basal command including therate and duration of along with a nominal bolus command and then waitfor a selected period of time and repeat a); and f) reducing the boluscommand by minimum bolus resolution and repeat step a) such that thecombination of the reduced bolus and a suitable temporary basal rateresults in an acceptable predicted glucose profile if calculating alower alternate temporary basal rate or a lower and shorter temporarybasal rate does not result in an acceptable future glucose level. Instill another aspect, the method further comprises alerting the user totake action to counter the effect of excessive insulin if an acceptableglucose profile cannot be obtained in step f) above.

In another aspect, the present invention includes a method forpredicting insulin needs at a future time to avoid unwanted out of rangealarms and adjusting current insulin delivery; comprising: providing acurrent glucose level; providing a future time when a predicted glucoselevel is required; determining the predicted level at the future timebased upon the current glucose level, a value for insulin on board,current bolus parameters and current parameters defining an acceptablerange of glucose levels; and adjusting insulin delivery to maintain theglucose level in a target range.

In yet another aspect, the present invention includes a method forreducing false hypoglycemic alarms in a system under closed loopcontrol; comprising: a) providing a current glucose level; b)determining if the first level is below a threshold level and if so,providing a further glucose level at the expiration of a selected periodof time; c) determining if the glucose level taken after the expirationof the selected period of time is below the threshold level, and if so,alerting the user of a low glucose condition if the time betweenproviding the two glucose levels is greater than a selected duration oftime, and if not, repeating c) until either the time since the currentglucose level and the last further glucose level exceeds the selectedduration of time or the last further glucose level is above thethreshold level.

In yet another aspect, the present invention includes a method ofadjusting glucose level alarm thresholds and alarm enunciation delaytimes in a system using CGM and insulin delivery system information,comprising using a model based state estimation, determining a predictedfuture glucose level and alerting a user only if the predicted futureglucose level falls outside of a predetermined acceptable range. In analternative aspect, the model based state estimation is a Kalman filter.In still another alternative aspect, the model based state estimationassesses the likelihood that a CGM measurement that exceeds a high orlow threshold is due to a true event. In yet another alternative aspect,the model based state estimation assesses the likelihood that a CGMmeasurement that exceeds a high or low threshold is due to a sensorartifact.

In still another aspect, the likelihood is determined by comparing thedifference between the latest CGM measurement and interstitial glucosecomputed by the model prior to the latest CGM measurement; and in afurther aspect, the method comprises adjusting the glucose alarmenunciation by adjusting the threshold level and duration in which theCGM measurement exceeds a given threshold before an alarm is enunciated.

In yet another aspect, where a decreasing CGM signal close to a lowthreshold alarm value that is not accompanied by a corresponding amountof insulin history will result in a low threshold alarm being made lesssensitive by lowering the threshold value and/or increasing the durationof delay before the CGM signal results in enunciation of a low thresholdalarm. In an alternative aspect, where a decreasing CGM signal close toa low threshold alarm value that is accompanied by an insulin historythat should have generated a much lower CGM value than is measuredresults in a low threshold alarm being made more sensitive by increasingthe threshold value and/or decreasing the duration of delay before theCGM signal results in the enunciation of a low threshold alarm. In stillanother alternative aspect, where an increasing CGM signal close to ahigh threshold alarm value that is not accompanied by an appreciableamount of insulin history results in a high threshold alarm being mademore sensitive by lowering the threshold value and/or decreasing theduration of delay before the CGM signal results in the enunciation of ahigh threshold alarm. In yet another alternative aspect, where anincreasing CGM signal close to a high threshold alarm value that isaccompanied by an appreciable amount of insulin history results in ahigh threshold alarm being made less sensitive by increasing thethreshold value and/or increasing the duration of delay before the CGMsignal results in the enunciation of a high threshold alarm.

In another aspect, the present invention a method of determining alatest insulin delivery amount and a temporary insulin delivery rate tobe delivered when a closed loop insulin delivery system terminatesunexpectedly, comprising a) providing a glucose level and predicting afuture glucose level in order to determine the appropriate insulinamount for the latest control action, and assuming that this commandedis immediately followed by open loop control where the pre-programmedtemporary basal rate will be in effect thereafter; b) analyzing thefuture glucose level using this latest insulin amount plus a futuretemporary basal rate to determine if the future glucose level isacceptable, and if so, waiting for a selected period of time andrepeating a); c) if the glucose level of b) is not acceptable, computingan alternate maximum temporary basal delivery amount that is lower thanthe previously assumed basal rate, such that the predicted futureglucose level is acceptable, and if so, providing a temporary basalcommand at the computed basal rate and duration, and predicting a futureglucose level; and if so, waiting for a selected period of time andrepeating a); d) if the predicted future glucose level is unacceptable,projecting a future glucose level using the lowest temporary basaldelivery rate computable in c) and a maximum duration that is shorterthan the maximum delivery duration, and, if the future glucose level isacceptable, providing a temporary basal command including the rate andduration of along with a nominal latest insulin delivery command andthen wait for a selected period of time and repeat a); and f) reducingthe latest insulin delivery command by a predetermined minimum insulindelivery resolution and repeat a) such that the combination of thereduced latest insulin delivery amount and a suitable temporary basalrate results in an acceptable predicted glucose profile if calculating alower alternate temporary basal rate or a lower and shorter temporarybasal rate does not result in an acceptable future glucose level.

Other features and advantages of the invention will become apparent fromthe following detailed description, taken in conjunction with theaccompanying drawings, which illustrate, by way of example, the featuresof the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating an exemplary embodiment of acontroller and its various components in operable communication with oneor more medical devices, such as a glucose monitor or drug deliverypump, and optionally, in operable communication with a remote controllerdevice.

FIG. 2 is a graphical representation of a glucose profile showingglucose level measured using a CGM sensor as a function of time, andalso showing the variation of the glucose level as function ofcarbohydrate intake and insulin administration.

FIG. 3 is a block diagram illustrating an embodiment of the presentinvention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

For the purposes of promoting an understanding of the principles of theinvention, reference will now be made to a number of illustrativeembodiments shown in the attached drawings and specific language will beused to describe the same. It will be understood that throughout thisdocument, the terms “user” and “patient” are used interchangeably.

Referring now to FIG. 1, a block diagram of one illustrative embodimentof a system 10 for determining drug administration information is shown.In the illustrated embodiment, the system 10 includes an electronicdevice 12, which may be handheld, having a processor 14 in datacommunication with a memory unit 16, an input device 18, a display 20,and a communication input/output unit 24. The electronic device 12 maybe provided in the form of a general purpose computer, central server,personal computer (PC), lap top or notebook computer, personal dataassistant (PDA), programmable telephone or cellular phone or otherhand-held device, external infusion pump, glucose meter, analyte sensingsystem, or the like. The electronic device 12 may be configured tooperate in accordance with one or more conventional operating systemsincluding for example, but not limited to, the Windows® operating system(distributed by Microsoft Corporation), the Linux operating system, theMac OS® (distributed by Apple, Inc.) and embedded operating systems suchas the QNX® operating system (distributed by QNX Software Systems), theeCOS® operating system (distributed by eCosCentric Limited), Windows CE®(distributed by Microsoft Corporation) and the Palm® operating system(distributed by Palm Inc.), and may be configured to process dataaccording to one or more conventional internet protocols for example,but not limited to, NetBios, TCP/IP and AppleTalk® (Apple, Inc.). In anycase, the electronic device 12 forms part of a fully closed-loop, semiclosed-loop, or open loop diabetes control system.

The processor 14 is microprocessor-based, although processor 14 mayalternatively be formed of one or more general purpose and/orapplication specific circuits and operable as described hereinafter. Theprocessor 14 is programmed using appropriate software commands that maybe stored in the memory or communicated to the processor 14 as needed.The memory unit 16 includes sufficient capacity to store data, one ormore software algorithms executable by the processor 14 and other data.The memory unit 16 may include one or more conventional memory or otherdata storage devices. Electronic device 12 may also include anintegrated glucose meter for use in calibrating a continuous glucosemonitor (CGM) or for calculating insulin amounts for bolus delivery.

The input device 18 may be used in a conventional manner to input and/ormodify data. The display 20 is also included for viewing informationrelating to operation of the device 12 and/or system 10. Such a displaymay be a conventional display device including for example, but notlimited to, a light emitting diode (LED) display, a liquid crystaldisplay (LCD), a cathode ray tube (CRT) display, or the like.Alternatively or additionally, the display 20 may be or include anaudible display configured to communicate information to a user, anotherperson, or another electronic system having audio recognitioncapabilities via one or more coded patterns, vibrations, synthesizedvoice responses, or the like. Alternatively or additionally, the display20 may be or include one or more tactile indicators configured todisplay or annunciate tactile information that may be discerned by theuser or another person.

The input device 18 may be or include a conventional keyboard or keypadfor entering alphanumeric data into the processor 14. Such a keyboard orkeypad may include one or more keys or buttons configured with one ormore tactile indicators to allow users with poor eyesight to find andselect an appropriate one or more of the keys, and/or to allow users tofind and select an appropriate one or more of the keys in poor lightingconditions. Alternatively or additionally, the input device 18 may be orinclude a conventional mouse or other conventional point and clickdevice for selecting information presented on the display 20.Alternatively or additionally, the input device 18 may include thedisplay 20 configured as a graphical user interface (GUI). In thisembodiment, the display 20 may include one or more selectable inputsthat a user may select by touching an appropriate portion of the display20 using an appropriate implement. Alternatively, the display 20 may beconfigured as a touch-screen capable of responding to user activationto, for example, enter data or select device functions.

Alternatively, the input device 18 may also include a number of switchesor buttons that may be activated by a user to select correspondingoperational features of the device 12 and/or system 10. Input device 18may also be or include voice-activated circuitry responsive to voicecommands to provide corresponding input data to the processor 14. In anycase, the input device 18 and/or display 20 may be included with orseparate from the electronic device 12.

System 10 may also include a number of medical devices which carry outvarious functions, for example, but not limited to, monitoring, sensing,diagnostic, communication and treatment functions. In such embodiments,any of the one or more of the medical devices may be implanted withinthe user's body, coupled externally to the user's body (e.g., such as aninfusion pump), or separate from the user's body. Alternatively oradditionally, one or more of the medical devices may be mounted toand/or form part of the electronic device 12. Typically, the medicaldevices are each configured to communicate wirelessly with thecommunication I/O unit 24 of the electronic device 12 via one of acorresponding number of wireless communication links.

The wireless communications between the various components of the system10 may be one-way or two-way. The form of wireless communication usedmay include, but is not limited to, radio frequency (RF) communication,infrared (IR) communication, Wi-Fi, RFID (inductive coupling)communication, acoustic communication, capacitive signaling (through aconductive body), galvanic signaling (through a conductive body), or thelike. In any such case, the electronic device 12 and each of the medicaldevices include conventional circuitry for conducting such wirelesscommunications circuit. Alternatively, one or more of the medicaldevices may be configured to communicate with the electronic device 12via one or more conventional serial or parallel configured hardwireconnections therebetween.

Each of the one or more medical devices 26 may include one or more of aconventional processing unit 52, conventional input/output circuitryand/or devices 56, 58 communication ports 60 and one or more suitabledata and/or program storage devices 58. It will be understood that notall medical devices 26 will have the same componentry, but rather willonly have the components necessary to carry out the designed function ofthe medical device. For example, in one embodiment, a medical device 26may be capable of integration with electronic device 12 and remotedevice 30. In another embodiment, medical device may also be capable ofstand-alone operation, should communication with electronic device 12 orremote device 30 be interrupted. In another embodiment, medical device26 may include processor, memory and communication capability, but doesnot have a display 58 or input 56. In still another embodiment, themedical device 26 may include an input 56, but lack a display 58.

In some embodiments, the system 10 may alternatively or additionallyinclude a remote device 30. The remote device 30 may include a processor32, which may be identical or similar to the processor 14, a memory orother data storage unit 34, an input device 36, which may be or includeany one or more of the input devices described hereinabove with respectto the input device 18, a display unit 38, which may be or include anyone or more of the display units described hereinabove with respect tothe display unit 20, and communication I/O circuitry 40. The remotedevice 30 may be configured to communicate with the electronic device 12or medical devices(s) 26 via any wired or wireless communicationinterface 42, which may be or include any of the communicationinterfaces or links described hereinabove. Although not shown, remotedevice 30 may also be configured to communicate directly with one ormore medical devices 26, instead of communicating with the medicaldevice 26 through electronic device 12.

The system 10 illustrated in FIG. 1 is, or forms part of, a fullyclosed-loop, semi closed-loop, or open loop diabetes controlarrangement. In this regard, the system 10 requires user input of someamount of information from which the system 10 determines, at least inpart, insulin bolus administration information. Such insulin bolusadministration information may be or include, for example, insulin bolusquantity or quantities, bolus type, insulin bolus delivery time, timesor intervals (e.g., single delivery, multiple discrete deliveries,continuous delivery, etc.), and the like. Examples of user suppliedinformation may be, for example but not limited to, user glucoseconcentration, interstitial glucose level information, informationrelating to a meal or snack that has been ingested, is being ingested,or is to be ingested sometime in the future, user exercise information,user stress information, user illness information, information relatingto the user's menstrual cycle, and the like. In any case, the system 10includes a delivery mechanism for delivering controlled amounts of adrug; such as, for example, insulin, glucagon, incretin, or the like,and/or offering an alternatively actionable therapy recommendation tothe user via the display 20, such as, for example, directions orinstructions related to ingesting carbohydrates, exercising, and thelike.

The system 10 may be provided in any of a variety of configurations, andexamples of some such configurations will now be described. It will beunderstood, however, that the following examples are provided merely forillustrative purposes, and should not be considered limiting in any way.Those skilled in the art may recognize other possible implementations ofa fully closed-loop, semi closed-loop, or open loop diabetes controlarrangement, and any such other implementations are contemplated by thisdisclosure.

In a first exemplary implementation of the system 10, the electronicdevice 12 is provided in the form of an insulin pump configured to beworn externally to the user's body and also configured to controllablydeliver insulin to the user's body. In this example, the medical devices26 may include one or more implanted sensors and/or sensor techniquesfor providing information relating to the physiological condition of theuser. Examples of such implanted sensors may include, but should not belimited to, a glucose sensor, a body temperature sensor, a bloodpressure sensor, a heart rate sensor, one or more bio-markers configuredto capture one or more physiological states of the body, such as, forexample, HBAlC, or the like.

In implementations that include an implanted glucose sensor, the system10 may be a fully closed-loop system operable in a conventional mannerto automatically monitor glucose and deliver insulin, as appropriate, tomaintain glucose at desired levels. The various medical devices mayalternatively or additionally include one or more sensors or sensingsystems that are external to the user's body and/or sensor techniquesfor providing information relating to the physiological condition of theuser. Examples of such sensors or sensing systems may include, butshould not be limited to, a glucose strip sensor/meter, a bodytemperature sensor, a blood pressure sensor, a heart rate sensor, one ormore bio-markers configured to capture one or more physiological statesof the body, such as, for example, HBAlC, or the like.

In implementations that include an external glucose sensor, the system10 may be a closed-loop, semi closed-loop, or open loop system operablein a conventional manner to deliver insulin, as appropriate, based onglucose information provided thereto by the user. Information providedby any such sensors and/or sensor techniques may be communicated to thesystem 10 using any one or more conventional wired or wirelesscommunication techniques. In this exemplary implementation, the remotedevice 30 may also be included in the form of a handheld or otherwiseportable electronic device configured to communicate information toand/or from the electronic device 12.

In a second exemplary implementation of the system 10, the electronicdevice 12 is provided in the form of a handheld remote device, such as aPDA, programmable cellular phone, or other handheld device. In thisexample, the medical devices 26 include at least one conventionalimplantable or externally worn drug pump. In one embodiment of thisexample, an insulin pump is configured to controllably deliver insulinto the user's body. In this embodiment, the insulin pump is configuredto wirelessly transmit information relating to insulin delivery to thehandheld device 12. The handheld device 12 is configured to monitorinsulin delivery by the pump, and may further be configured to determineand recommend insulin bolus amounts, carbohydrate intake, exercise, andthe like. The system 10 may or may not be configured in this embodimentto provide for transmission of wireless information from the handhelddevice 12 to the insulin pump.

In an alternate embodiment of this example, the handheld device 12 isconfigured to control insulin delivery to the user by determininginsulin delivery commands and transmitting such commands to the insulinpump. The insulin pump, in turn, is configured to receive the insulindelivery commands from the handheld device 12, and to deliver insulin tothe user according to the commands. The insulin pump, in thisembodiment, may or may not further process the insulin pump commandsprovided by the handheld unit 12. In any case, the system 10 willtypically be configured in this embodiment to provide for transmissionof wireless information from the insulin pump back to the handhelddevice 12 to thereby allow for monitoring of pump operation. In eitherembodiment of this example, the system 10 may further include one ormore implanted and/or external sensors of the type described in theprevious example. In this exemplary implementation, a remote device 30may also be included in the form of, for example, a PC, PDA,programmable cellular phone, laptop or notebook computer configured tocommunicate information to and/or from the electronic device 12.

Those skilled in the art will recognize other possible implementationsof a fully closed-loop, semi closed-loop, or open loop diabetes controlarrangement using at least some of the components of the system 10illustrated in FIG. 1. For example, the electronic device 12 in one ormore of the above examples may be provided in the form of a PDA,programmable cellular phone, laptop, notebook or personal computerconfigured to communicate with one or more of the medical devices 26, atleast one of which is an insulin delivery system, to monitor and/orcontrol the delivery of insulin to the user. As another example, theremote device 30 may be configured to communicate with the electronicdevice 12 and/or one or more of the medical devices 26, to controland/or monitor insulin delivery to the patient, and/or to transfer oneor more software programs and/or data to the electronic device 12. Theremote device 30 may reside in a caregiver's office or other remotelocation, and communication between the remote device and any componentof the system 10 may be accomplished via an intranet, internet (such as,for example, through the world-wide-web), cellular, telephone modem, RF,or other communication link. Any one or more conventional internetprotocols may be used in such communications. Alternatively oradditionally, any conventional mobile content delivery system; such as,for example, Wi-Fi, WiMAX, short message system (SMS), or otherconventional message scheme may be used to provide for communicationbetween devices comprising the system 10.

Generally, the concentration of glucose in a person changes as a resultof one or more external influences such as meals and exercise, and alsochanges resulting from various physiological mechanisms such as stress,illness, menstrual cycle and the like. In a person with diabetes, suchchanges can necessitate monitoring the person's glucose level andadministering insulin or other glucose level altering drug, such as, forexample, a glucose lowering or raising drug, as needed to maintain theperson's glucose level within a desired range. In any of the aboveexamples, the system 10 is thus configured to determine, based on someamount of patient-specific information, an appropriate amount, typeand/or timing of insulin or other glucose level altering drug toadminister in order to maintain normal glucose levels without causinghypoglycemia or hyperglycemia. In some embodiments, the system 10 isconfigured to control one or more external insulin pumps, such as, forexample, subcutaneous, transcutaneous or transdermal pumps, and/orimplanted insulin pumps to automatically infuse or otherwise supply theappropriate amount and type of insulin to the user's body in the form ofone or more insulin boluses.

In other embodiments, the system 10 is configured to display orotherwise notify the user of the appropriate amount, type, and/or timingof insulin in the form of an insulin delivery or administrationrecommendation or instruction. In such embodiments, the hardware and/orsoftware forming system 10 allows the user to accept the recommendedinsulin amount, type, and/or timing, or to reject it. If therecommendation is accepted by the user, the system 10, in oneembodiment, automatically infuses or otherwise provides the appropriateamount and type of insulin to the user's body in the form of one or moreinsulin boluses. If, on the other hand, the user rejects the insulinrecommendation, the hardware and/or software forming system 10 allowsthe user to override the system 10 and manually enter values for insulinbolus quantity, type, and/or timing in the system. The system 10 is thusconfigured by the user to automatically infuse or otherwise provide theuser specified amount, type, and/or timing of insulin to the user's bodyin the form of one or more insulin boluses.

Alternatively, the appropriate amount and type of insulin correspondingto the insulin recommendation displayed by the system 10 may be manuallyinjected into, or otherwise administered to, the user's body. It will beunderstood, however, that the system 10 may alternatively oradditionally be configured in like manner to determine, recommend,and/or deliver other types of medication to a patient.

The system 10 is operable, as just described, to determine and eitherrecommend or administer an appropriate amount of insulin or otherglucose level lowering drug to the patient in the form of one or moreinsulin boluses. In order to determine appropriate amounts of insulin tobe delivered or administered to the user to bring the user's glucoselevel within an acceptable range, the system 10 requires at least someinformation relating to one or more external influences and/or variousphysiological mechanisms associated with the user. For example, if theuser is about to ingest, is ingesting, or has recently ingested, a mealor snack, the system 10 generally requires some information relating tothe meal or snack to determine an appropriate amount, type and/or timingof one or more meal compensation boluses of insulin. When a personingests food in the form of a meal or snack, the person's body reacts byabsorbing glucose from the meal or snack over time. For purposes of thisdocument, any ingesting of food may be referred to hereinafter as a“meal,” and the term “meal” therefore encompasses traditional meals,such as, for example, breakfast, lunch and dinner, as well asintermediate snacks, drinks, and the like.

FIG. 2 depicts a typical glucose absorption profile 200 for a usermeasured using a CGM sensor. The graph 205 plots the measured glucoselevel as a function of time. This profile shows the effect on glucoselevel of various actions, such as carbohydrate intake 210, and thedelivery of rapid acting insulin 210 and long acting insulin 230.

The general shape of a glucose absorption profile for any person risesfollowing ingestion of the meal, peaks at some measurable time followingthe meal, and then decreases thereafter. The speed, that is, the ratefrom beginning to completion, of any one glucose absorption profiletypically varies for a person by meal composition, meal type or time(such as, for example, breakfast, lunch, dinner, or snack) and/oraccording to one or more other factors, and may also vary fromday-to-day under otherwise identical meal circumstances. Generally, theinformation relating to such meal intake information supplied by theuser to the system 10 should contain, either explicitly or implicitly,an estimate of the carbohydrate content of the meal or snack,corresponding to the amount of carbohydrates that the user is about toingest, is ingesting, or has recently ingested, as well as an estimateof the speed of overall glucose absorption from the meal by the user.

The estimate of the amount of carbohydrates that the patient is about toingest, is ingesting, or has recently ingested, may be provided by theuser in any of various forms. Examples include, but are not limited to,a direct estimate of carbohydrate weight (such as, for example, in unitsof grams or other convenient weight measure), an amount of carbohydratesrelative to a reference amount (such as, for example, dimensionless), anestimate of meal or snack size (such as, for example, dimensionless),and an estimate of meal or snack size relative to a reference meal orsnack size (such as, for example, dimensionless). Other forms ofproviding for user input of carbohydrate content of a meal or snack willoccur to those skilled in the art, and any such other forms arecontemplated by this disclosure.

The estimate of the speed of overall glucose absorption from the meal bythe user may likewise be provided by the user in any of various forms.For example, for a specified value of the expected speed of overallglucose absorption, the glucose absorption profile captures the speed ofabsorption of the meal taken by the user. As another example, the speedof overall glucose absorption from the meal by the user also includestime duration between ingesting of the meal by a user and the peakglucose absorption of the meal by that user, which captures the durationof the meal taken by the user. The speed of overall glucose absorptionmay thus be expressed in the form of meal speed or duration. Examples ofthe expected speed of overall glucose absorption parameter in this casemay include, but are not limited to, a compound parameter correspondingto an estimate of the meal speed or duration (such as, for example,units of time), a compound parameter corresponding to meal speed orduration relative to a reference meal speed or duration (such as, forexample, dimensionless), or the like.

As another example of providing the estimate of the expected speed ofoverall glucose absorption parameter, the shape and duration of theglucose absorption profile may be mapped to the composition of the meal.Examples of the expected speed of overall glucose absorption parameterin this case may include, but are not limited to, an estimate of fatamount, protein amount and carbohydrate amount (such as, for example, inunits of grams) in conjunction with a carbohydrate content estimate inthe form of meal size or relative meal size, an estimate of fat amount,protein amount and carbohydrate amount relative to reference fat,protein and carbohydrate amounts in conjunction with a carbohydratecontent estimate in the form of meal size or relative meal size, and anestimate of a total glycemic index of the meal or snack (such as, forexample, dimensionless), wherein the term “total glycemic index” isdefined for purposes of this document as a parameter that ranks mealsand snacks by the speed at which the meals or snacks cause the user'sglucose level to rise. Thus, for example, a meal or snack having a lowglycemic index produces a gradual rise in glucose level whereas a mealor snack having a high glycemic index produces a fast rise in glucoselevel. One exemplary measure of total glycemic index may be, but is notlimited to, the ratio of carbohydrates absorbed from the meal and areference value, such as, for example, derived from pure sugar or whitebread, over a specified time period, such as, for example, 2 hours.Other forms of providing for user input of the expected overall speed ofglucose absorption from the meal by the patient, and/or for providingfor user input of the expected shape and duration of the glucoseabsorption profile generally will occur to those skilled in the art, andany such other forms are contemplated by this disclosure.

Generally, the concentration of glucose in a person with diabeteschanges as a result of one or more external influences such as mealsand/or exercise, and may also change resulting from variousphysiological mechanisms such as stress, menstrual cycle and/or illness.In any of the above examples, the system 10 responds to the measuredglucose by determining the appropriate amount of insulin to administerin order to maintain normal glucose levels without causing hypoglycemia.In some embodiments, the system 10 is implemented as a discrete systemwith an appropriate sampling rate, which may be periodic, aperiodic ortriggered, although other continuous systems or hybrid systems mayalternatively be implemented as described above.

As one example of a conventional diabetes control system, one or moresoftware algorithms may include a collection of rule sets which use (1)glucose information, (2) insulin delivery information, and/or (3) userinputs such as meal intake, exercise, stress, illness and/or otherphysiological properties to provide therapy, and the like, to manage theuser's glucose level. The rule sets are generally based on observationsand clinical practices as well as mathematical models derived through orbased on analysis of physiological mechanisms obtained from clinicalstudies. In the exemplary system, models of insulin pharmacokinetics andpharmacodynamics, glucose pharmacodynamics, meal absorption and exerciseresponses of individual patients are used to determine the timing andthe amount of insulin to be delivered. A learning module may be providedto allow adjustment of the model parameters when the patient's overallperformance metric degrades such as, for example, adaptive algorithms,using Bayesian estimates, may be implemented. An analysis model may alsobe incorporated which oversees the learning to accept or rejectlearning. Adjustments are achieved utilizing heuristics, rules,formulae, minimization of cost function(s) or tables (such as, forexample, gain scheduling).

Predictive models can be programmed into the processor(s) of the systemusing appropriate embedded or inputted software to predict the outcomeof adding a controlled amount of insulin or other drug to a user interms of the an expected glucose value. The structures and parameters ofthe models define the anticipated behavior.

Any of a variety of conventional controller design methodologies, suchas PID systems, full state feedback systems with state estimators,output feedback systems, LQG (Linear-Quadratic-Gaussian) controllers,LQR (Linear-Quadratic-Regulator) controllers, eigenvalue/eigenstructurecontroller systems, and the like, could be used to design algorithms toperform physiological control. They typically function by usinginformation derived from physiological measurements and/or user inputsto determine the appropriate control action to use. While the simplerforms of such controllers use fixed parameters (and therefore rules) forcomputing the magnitude of control action, the parameters in moresophisticated forms of such controllers may use one or more dynamicparameters. The one or more dynamic parameters could, for example, takethe form of one or more continuously or discretely adjustable gainvalues. Specific rules for adjusting such gains could, for example, bedefined either on an individual basis or on the basis of a userpopulation, and in either case will typically be derived according toone or more mathematical models. Such gains are typically scheduledaccording to one or more rule sets designed to cover the expectedoperating ranges in which operation is typically nonlinear and variable,thereby reducing sources of error.

Model based control systems, such as those utilizing model predictivecontrol algorithms, can be constructed as a black box wherein equationsand parameters have no strict analogs in physiology. Rather, such modelsmay instead be representations that are adequate for the purpose ofphysiological control. The parameters are typically determined frommeasurements of physiological parameters such as glucose level, insulinconcentration, and the like, and from physiological inputs such as foodintake, alcohol intake, insulin doses, and the like, and also fromphysiological states such as stress level, exercise intensity andduration, menstrual cycle phase, and the like. These models are used toestimate current glucose level or to predict future glucose levels. Suchmodels may also take into account unused insulin remaining in the userafter a bolus of insulin is given, for example, in anticipation of ameal. Such unused insulin will be variously described as unused,remaining, or “insulin on board.”

Insulin therapy is derived by the system based on the model's ability topredict glucose levels for various inputs. Other conventional modelingtechniques may be additionally or alternatively used to predict glucoselevels, including for example, but not limited to, building models fromfirst principles.

In a system as described above, the controller is typically programmedto provide a “basal rate” of insulin delivery or administration. Such abasal rate is the rate of continuous supply of insulin by an insulindelivery device such as a pump that is used to maintain a desiredglucose level in the user. Periodically, due to various events thataffect the metabolism of a user, such as eating a meal or engaging inexercise, a “bolus” delivery of insulin is required. A “bolus” isdefined as a specific amount of insulin that is required to raise theblood concentration of insulin to an effective level to counteract theaffects of the ingestion of carbohydrates during a meal and also takesinto account the affects of exercise on the glucose level of the user.

As described above, an analyte monitor may be used to continuouslymonitor the glucose level of a user. The controller is programmed withappropriate software and uses models as described above to predict theaffect of carbohydrate ingestion and exercise, among other factors, onthe predicted level of glucose of the user at a selected time. Such amodel must also take into account the amount of insulin remaining in theblood stream from a previous bolus or basal rate infusion of insulinwhen determining whether or not to provide a bolus of insulin to theuser.

In a typical situation, an insulin pump normally delivers insulinwithout user intervention when delivering the insulin at the basalinsulin delivery rate. At times, however, the pump may detect conditionsthat warrant providing an alarm or other signal to the user thatintervention in the insulin delivery by the user is necessary. Dependingon the conditions and the user's response, the controller may instructthe pump to stop delivering insulin.

When insulin delivery is stopped, the user will eventually need torestart insulin delivery. In view of the period of time during whichinsulin delivery was stopped, the user may need to deliver a correctionbolus of insulin to bring their glucose level back within an acceptablerange. The volume of the insulin bolus is calculated by the user fromtheir current glucose level and their experience with managing theirdiabetes. For example, users who have experience in managing theirdiabetes are typically able to estimate the various factors that need tobe considered in calculating a corrective bolus dosage of insulin.

In one example, the size of the corrective bolus required to maintainthe user in euglycemia is related to the manner and duration in whichdelivery of insulin was stopped. For example, if insulin delivery wasstopped for a few minutes, perhaps no corrective bolus of insulin isrequired. However, if insulin delivery is stopped for several hours, asignificant bolus of insulin may be required to bring the user's glucoselevel into an acceptable range.

The controller of the system monitors the insulin pump and when the pumpdetermines that the user wants to restart the pump, the pump may eitherconfirm that the user wants to restart basal rate delivery of insulin,or it may prompt the user to administer a manual bolus of insulin.

In one embodiment of the invention, the controller and/or pump has amemory that stores information related to the history of the user'sglucose levels and various actions or events that have been taken toadjust those levels, such as the rate of basal delivery of insulin, theamount of the last insulin bolus delivery, and the time between variousevents or user actions. The controller and/or pump may also store thetime that has elapsed since the pump was stopped. Additional factorsthat may be considered include the user's insulin sensitivity, theamount of insulin that may remain in the user's blood stream since thelast basal or bolus insulin delivery and whether or not an event oraction may have incurred that would cause the basal rate of insulindelivery to have changed since the pump was stopped.

When the user desires to restart the pump, the controller and/or pumpmay, using the data programmed within the memory regarding the user'shistory of insulin delivery and glucose levels resulting therefrom,calculate a bolus volume of insulin to deliver using a model such as setforth as:

Remaining insulin=delivered_volume×(IATIME−time)/IATIME,

Where:

Delivered_volume is the amount of insulin delivered,

time is the time since the insulin was delivered, and

IATIME is the user's insulin action time, which is a measure of how longinsulin remains active in an individual user's body.

Those skilled in the art will understand that other models can be usedto perform this estimation, such as, for example, the decayingexponential model or model using an S-model decay.

For basal delivery, the times since the insulin was last delivered, orthe age of the delivery, is not a constant. The calculation is aconvolution of the basal profile function and the linear decay function.

In practice, basal insulin delivery is not delivered continuously, butinstead is accumulated and delivered at discrete times. For example, anexemplary insulin pump may be programmed to deliver three minutes ofbasal rate insulin delivery spaced three minutes apart. This simplifiesthe above calculation to the dot product of two vectors. For example,

-   -   D=vector of deliveries that were not performed, oldest to        newest. For example,    -   D=(0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.5, 0.5,        0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5) which represents 20        deliveries of 0.3 and 0.5 units spaced three minutes apart.    -   Similarly, T=vector or time multipliers.        -   For example, if the insulin action time of the patient is 60            minutes and delivery has been stopped for 42 minutes, then:    -   T equals (0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.35, 0.40, 0.45,        0.50, 0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95,        1.00).    -   The dot product of D*T equal 4.39 units.

Thus, for this example, the user will need to either manually administeror program the pump to administer 4.39 units of insulin, the bolusvolume that will provide the same value for the insulin onboard for theuser had the basal delivery of insulin not been stopped.

In another embodiment of the present invention using a closed loopedcontrol system, the controller or pump may be programmed to perform amodel-based calculation of transitory insulin using an insulin boluscommand as the nominal input for the model. This process provides ameans to use model-based calculation of insulin onboard (IOB) pastinsulin delivery information, and past and present glucose informationand predicted glucose profile over a near-future horizon to determine asafe amount and duration of basal rate in the event that a closed loopsystem that normally uses bolus insulin deliver terminates its operationunexpectedly.

Automated closed loop systems that regulate glucose levels by usinginsulin delivery have to account for instances when the closed loopsystem terminates and switches to open loop control. For users withinsulin pumps, open-loop operation typically includes a pre-programmedinsulin basal rate as well as a bolus insulin delivery rate administeredin response to known events, such as a meal. When a system transitionsfrom open to closed loop, past insulin delivery information is availablefrom the memory and can be used by the closed loop controller todetermine the best and safest insulin delivery profile for the user.

One hazard mitigated by this process is related to the transition fromclosed loop to open loop operation, such as, for example, in the casewhere a controller under closed loop control has determined a series ofinsulin commands that may require subsequent insulin deliveries to belower than the open loop pre-programmed basal insulin delivery rate. Aslong as the system remains in closed loop operation, this is not anissue. However, should the system transition to open loop operation,having the pump deliver insulin at the pre-programmed basal rate couldresult in unwanted hypoglycemia if the controller previously ordered thepump to deliver insulin at a rate and duration that resulted in a largeresidual IOB with a plan to control the delivery in the future tosignificantly reduce the insulin delivery at a rate below thepre-programmed basal rate.

One embodiment of the invention addresses the situation where the closedloop system operates by delivering bolus insulin commands at a fixedinterval in time, and the closed-loop system periodically obtainsglucose measurement from a glucose measuring device. Such a system isalso capable of issuing a temporary basal rate command to the pump witha specified amount and duration in which the basal command should applysince the command was issued. When the duration of such a demandexpires, the system reverts to the pre-programmed basal rate.

As used in this description of the various embodiments of the invention,the latest command intended for normal operation of the system isdescribed in terms of “bolus commands.” Alternatively, the safetycommand intended to be used when closed loop operation of the system isinterrupted is described in terms of a “temporary basal rate” command.The replacement of the normal operation command in terms of bolus withbasal rate does not change the mechanism of the various embodiments ofthe invention. Using bolus and basal rate for the normal operation andthe safety-related commands clarifies the roles of those commands in thedescription of the various embodiments of the invention included herein.

In another embodiment of the invention, the closed loop system is ableto track the IOB amount by utilizing insulin pharmacokinetic andpharmacodynamic models, and by keeping track of insulin delivery datacorresponding to the actual delivery of insulin to the user. Thisdelivery data includes bolus and basal insulin amounts commanded by theuser or by the automated closed loop controller.

For example, the model used by the controller to calculate insulindelivery rates may utilize a pharmacokinetic model, such as a modifiedversion of a model used by Hovorka et al.:

$\frac{\partial\left( {i\; 1(t)} \right)}{\partial t} = {\frac{{- 1}(t)}{tau\_ i} + {u(t)}}$$\frac{\partial\left( {i\; 2(t)} \right)}{\partial(t)} = {- \frac{\left\lbrack {{i\; 2(t)} - {i\; 1(t)}} \right\rbrack}{tau\_ i}}$${i(t)} = \frac{i\; 2(t)}{MCRWtau\_ i}$

Where:

(t) denotes variables and/or states that vary in time;

u(t) is the amount of insulin bolus given at any time t;

i1(t) and i2(t) are internal states of the insulin absorption;

i(t) is the plasma insulin concentration;

tau_i is the time-to-peak of insulin absorption;

MCR is the metabolic clearance rate; and

W is the user's weight.

An example of an insulin pharmacodynamic model that may be programmedinto the controller or pump using suitable software or hardware commandsis given by:

$\left. {\frac{\partial\left( {x(t)} \right)}{\partial t} = {{{- p}\; {1\left\lbrack {{x{()}}t} \right)}} - {i(t)}}} \right\rbrack$$\frac{\partial\left( {g(t)} \right)}{dt} = {- \begin{bmatrix}{{\left. {{Sg} + \left\lbrack {{Si} \cdot {x(t)}} \right\rbrack} \right\rbrack {g(t)}} =} \\{\left. {\left\lbrack {{Sg} \cdot g} \right)(t)} \right\rbrack + {{Sm} \cdot \frac{\partial\left( {{gm}(t)} \right)}{dt}}}\end{bmatrix}}$

Where:

Sg is the glucose clearance rated independent of insulin;

Si is the glucose clearance rate due to insulin;

g0(t) is a slowly varying equilibrium for the glucose clearanceindependent of insulin;

Sm is the glucose appearance constant due to meal absorption; and

$\frac{\partial\left( {{gm}(t)} \right.}{\partial(t)}$

is the rate of glucose appearance due to meal absorption.

In this model, the first equation governs the effective insulin×(t) overtime as a function of plasma insulin i(t), given a decay time constantof 1/p1. The second equation governs how glucose g(t) varies over timeas a function of many factors, including, for example, the insulinpharmacodynamics −Si×(t)g(t).

At any given time, the closed loop system is able to estimate the latestglucose by utilizing the IOB data, insulin history, glucosemeasurements, and a physiological model of glucose in response toinsulin and other measurable factors, such as exercise and meal estimateand/or announcements. Additionally, at any time, the closed loop systemin one embodiment of the invention is able to compute a desired boluscommand that would result in the present and projected glucose of theuser in a selected near future horizon falling within a specifiednominal target, or one that optimizes the present and projected glucosewith respect to some robust optimality criteria. This is a typicalprocess involved in automatic closed looped systems that aremodel-based, such as a model-based approach that falls under the modelpredictive control (MPC) architecture.

When the system receives a temporary basal command, the closed loopsystem may, given the IOB, insulin history, glucose history, predictedglucose (in the near future horizon), and pre-programmed basal insulindelivery rate, compute a temporary basal amount and duration such thatif the closed loop operation of the system terminates, the combinationof the basal rate of that amount and the specified duration and thesubsequent transition to the pre-programmed basal rate is such that thepredicted glucose value of the user in the foreseeable future horizonwill remain within a specified safe target. This safe target may bedifferent from the specified nominal target value for the optimalcalculation, in that it can be designed to be more conservative from ahazards prevention perspective.

An example of a process for determining a temporary basal rate ofinsulin delivery, along with the duration of that basal rate delivery,is illustrated by the diagram of FIG. 3. Appropriate software orhardware commands may be used to program the processor of the pumpand/or controller to carry out the illustrated steps. Using a heuristicprocess, a glucose value may be predicted into the near future horizonunder an assumption that the commanded bolus insulin delivery at presentis followed by an immediate transfer to the programmed basal rate. Inother words, the temporary basal rate candidate value calculated usingthe heuristic by the controller is identical to the pre-programmed basalrate.

Using this information as a starting point in box 310 as input into theselected model, a predicted glucose profile for a future time iscalculated in box 320. If an acceptable predicted glucose profileresults from this calculation in box 330, then there is no need to issuea temporary basal rate of any duration to maintain the user's glucoselevel within an acceptable range. When this is the case, the systemwaits until the next time an insulin command needs to be issued in box340. When the next insulin command is determined to be needed, theprocessor begins at box 310, and once again carries out the processwherein glucose is predicted into the near future horizon as statedabove.

If an acceptable predicted glucose profile does not result from thecalculation carried out by the processor of the controller, thetemporary basal insulin delivery rate is decreased by one value lowerfrom the previous temporary basal rate candidate in box 350. Theresolution of the basal rate for the particular pump and/or controllerand/or glucose sensor determines the size of the reduction of basal ratethat will be applied. This calculation may assume the maximum deliveryduration allowable by the system.

If this assumption results in an acceptable predicted glucose profile inbox 360, then a temporary basal insulin delivery command is sent usingthis basal rate and duration along with the nominal bolus command to thepump in box 370. The controller then waits until the next time aninsulin command needs to be issued, and then restarts the process at box310 again.

If an acceptable glucose profile is not calculated in box 360, theprocess keeps the same temporary basal rate as was used in box 350, andthe decreases the duration of the basal rate delivery by an amount thatis a function of system's resolution on command duration in box 380. Ifthis calculation results in an acceptable predicted glucose profile inbox 290, then a temporary basal command using this basal rate andduration along with the nominal bolus command is sent to the pump in box370. Again, the controller waits until the next time an insulin commandneeds to be issued in box 340. When that time occurs, the process beginsagain box 310.

The iterative process described above is continued until the lowestallowable basal rate of insulin delivery is reached. If this assumptiondoes not result in an acceptable predicted glucose profile, then thebolus command is reduced such that the combination of the reduced bolusrate and the temporary basal rate results in an acceptable predictedglucose profile. If this is not possible, then an alert is sent to theuser to take rescue carbohydrates or other actions that counteract theeffect of excessive insulin.

The purpose of the above-described process is to add an additionalsafety calculation layer for the process control provided by automatedclosed-loop algorithms such that the closed-loop system computes twoscenarios. First, the common scenario where insulin commands are issuedand acted upon without interruption in the foreseeable future. This isnormally computed by the automated closed-loop systems using model basedapproaches such as MPC. Second, the hazard-mitigated scenario where thesequence of insulin commands are abruptly interrupted after the latestcommand. The process set forth above addresses this scenario.

Using such a system, the embodiments of the present invention usemodel-based principles and available data to predict more than onescenario of insulin delivery such that when the periodic normal insulincommand is interrupted, the system does not cause an unwantedhypoglycemic hazard. Avoiding unwanted hypoglycemia is important inproviding proper control of glucose level in the diabetic user. Thevarious embodiments of the invention provide better hazard mitigationagainst the risk of hypoglycemia due to a combination of insulinstacking (where a user already has an amount of insulin on board, butadministers an additional bolus of insulin, often driving the user'sglucose level towards hypoglycemia) and termination of closed-loopcontrol. Utilizing a model-based approach improves the hazard mitigationcaused by interruption of the automated closed-loop system, even thoughthe interruption may have been accompanied by an alert/alarm or atemporary basal rate with a fixed duration.

In a CGM device such as the FreeStyle Navigator® Continuous GlucoseMonitoring System that is distributed by Abbott Diabetes Care, there isa mute alarm feature that allows the user to mute the alarm when it isnot easy for the user to respond to the alarm. Such alarms occur, forexample, when the user's glucose level is either in the hyperglycemicrange or, more importantly, in the hypoglycemic range.

For example, the user may choose to mute the alarm for the next twohours knowing that the user will be in a long meeting and does not wantthe alarm to disturb anyone. However, in the case of a low alarmsignifying hypoglycemia, muting the alarm may lead to failure of theuser to treat the hypoglycemic condition, which could be dangerous. Thesituation would be improved if at the time the user is muting the alarm,the system checks to determine the likelihood that the user may becomehypoglycemic within the period of time that the alarm is muted.Generally, the system calculates a projected low-glucose level using IOBand real-time information to fine tune the projection and providing analarm to indicate low glucose values. The problem with a persistentprojected alarm, however, is the additional user annoyance associatedwith false positives. A user-initiated approach allows the user todefine the time period that he wishes to have more precaution built intothe control system as opposed to the system simply providing apersistent alarm to the user indicating that the controller hasdetermined that some correction action is necessary, but at a time thata user is either unable or unwilling to take such action.

In one embodiment, the invention uses an overall strategy of potentiallow alarm detection to preempt pump control modification. Such adetermination is useful during activities or events such as where theuser goes to a long meeting or attends an event such as a movie,theatre, concert, or a long drive that may create a barrier fromdetecting and acting on a low-glucose level alarm. Another situationwhere the various embodiments of the invention are advantageous is wherethe user goes to bed at night and wishes to know whether a low glucoselevel alarm may sound during the night.

This embodiment of the invention includes a predictive alarm avoidancefeature that is described hereafter. When the user foresees that he willbe unavailable to act on an alarm in the near future, such as, forexample, in the case where the user knows he will enter a meeting withinthe next 30 minutes, the user initiates the process of analyzing hiscurrent CGM glucose level and pump calculated IOB information todetermine if the user's glucose level is likely be at in a range thatthe cause the device to produce an alarm during the meeting.

Using a controller that is programmed with appropriate software andhardware commands to carry out the functions required to perform thepredictive alarm avoidance embodiment, the user enters the time horizonmoving forward that he will be unavailable to take corrective actions ifan alarm is presented. This entry is similar to the entry for the numberof hours to mute an alarm in the current Freestyle Navigator® ContinuousGlucose Monitoring System.

Based on the time horizon entered by the user, and other informationfound in the memory associated with the CGM and pump device, forexample, but not limited to, the current CGM glucose level reading, thecurrent IOB reading, the current bolus calculator parameters, and thecurrent low and high reading settings, the processor calculates whetherthe user will be in one of three states in the future: a) a state wherehis glucose profile is adequate; b) in a carbohydrate deficient state,that is, a low glucose level state; and c) an insulin deficient state,that is, the user is in a hyperglycemic state during the time that hewill not be able to make an adjustment to his pump. The followingexample illustrates this process.

Example 1

Assuming a user wishes to avoid an alarm where, and at the time he iscommanding the controller to perform this calculation, the followingvalues are pertinent to the calculation:

-   -   target threshold: 110 mg/dL,    -   high alarm threshold: 240 mg/dL,    -   lower alarm threshold: 70 mg/dL;    -   carbohydrate ratio: 1 unit of insulin for 15 grams of carb;    -   insulin sensitivity factor (ISF): 1 unit of insulin for 50        mg/dL; and    -   insulin action time: 5 hours.

In the case where the user will be unavailable or unwilling to takecorrective action if he is presented with an alarm for the next threehours, the processor calculates a glucose level profile of the userutilizing the above factors to determine whether the user's glucoseprofile will stay in an acceptable range, or if the profile will resultin either a hypo- or hyper-glycemic state. In this case, with the abovefactors, the calculation reveals that the user would have an adequateglucose profile where the current CGM glucose value is 150 mg/dL and thecurrent IOB is 1.1 units. Using methods well known by those in the art,the calculations carried out by the processor show that in five hours,the user's glucose level will decrease by 55 mg/dL (IOB*ISF), which is aglucose decline rate of 11 mg/dL per hour. Thus, during the three hoursthat the user will be unavailable or unwilling to take action to correctan alarm, the user's glucose level is estimated to be approximately 117mg/dL (or, a 33 mg/dL decrease in glucose level from the user's currentglucose level), which, for this user, is an acceptable glucose level.

Now considering the case where the user's current CGM glucose value is150 mg/dL and the pump history (stored in the memory associated with thepump or controller) indicates a current IOB of 3.1 units. Using thesestarting values, the processor calculates that in five hours the user'sglucose level will decrease by 155 mg/dL, which is a glucose declinerate of 31 mg/dL per hour. Thus, if the user is unavailable or unwillingto take corrective action in the next three hours, his glucose levelwill fall to around 57 mg/dL (a 93 mg/dL decrease in glucose level fromthe user's current glucose level), which is a carbohydrate deficientstate.

Once the processor and controller knows that the user will be in acarbohydrate deficient state, the processor can recommend, for example,one or more of the following actions to the user using the display ofthe controller:

-   -   a) instruct the user to eat X grams of carbohydrates now or        later to avoid the low glucose level, the value of X being        calculated as X=(target minus future low)/ISF*carb ratio which        is equal to (110 minus 57)/50*1.5=15.9 grams of carbohydrates;        or    -   b) instruct the user to reduce the basal rate of his insulin        pump by using a temporary basal rate on the pump. The rate and        duration of the temporary basal race is determined by the user        using an interface on the device that can be interacted with by        the user to cause the processor of the device to compute the        temporary basal rate. For example, the controller may provide        the user with the information he needs to program the processor        of the device to reduce insulin delivery by X units per hour in        the next three hours to i) stay within the target glucose level        range, where X can be calculated as X=(target minus future        low)/ISF/time horizon which is equal to (110 minus 57)/50/3        equals 0.354 units per hour (high reduction) or ii) maintain the        user's glucose level above the low alarm threshold X=(low        threshold minus future low)/ISF/time horizon equal (70 minus        57)/50/3 equals 0.087 units per hour (lower reduction);    -   c) the user may also be given the option of increasing the time        horizon of the calculations, especially if the recommended        reduced insulin amount is greater than the current basal rate,        in order to bring about a more conservative reduction in the        basal rate. For example, instead of reducing the amount of        insulin delivered within the next three hours, the user may        extend the time of insulin delivery to five hours.

If the user is watching a movie in a theatre, for example, the user maychoose scenario a). If the user performs the calculation right beforegoing to bed, or before taking a short nap, then he may choose scenariob) (assuming that the user's basal rate is greater than 0.087 units perhour or 0.35 per hour).

In a further example, a user's initial CGM glucose level is 280 mg/dLand the pump history indicates that the user's current IOB is 3.1 units.In this case, the processor calculates that in five hours, the user'sglucose level will decrease by 155 mg/dL, which is a glucose leveldecline rate of 31 mg/dL per hour. With this glucose level decline rate,during the next three hours when the user is unavailable or unwilling totake corrective action, the user's glucose level is estimated by theprocessor to be around 187 mg/dL (a decrease of 93 mg/dL in glucoselevel from the user's current level), which could mean that the userwill be in an insulin deficient state.

Given this calculation, the controller may also determine whether or notmore insulin should be recommended to be taken by the user to avoid thispossibly insulin deficient state. In this case, in five hours, based onthe IOB, the user's glucose level can be estimated at 125 mg/dL, which aslightly above the user's target glucose level, so the controller andprocessor of the device may recommend slightly more insulin.

Alternatively, the device may recommend that the user does not need todo anything now or that he could choose to give himself a little moreinsulin (X units) using an extended bolus feature of the pump where:

X=the (predicted glucose level after insulin action time)−(the targetglucose level)/ISF which is equal to 0.3 units, and

Time duration=the user entered time horizon which is equal to threehours.

An embodiment of the controller of the present invention includes anappropriate User Interface (UI). This user interface is presented by theprocessor to the user and is formed by processor in accordance withappropriate software commands that have programmed the processor tooperate accordingly. The user interface is user friendly to facilitatethe user in making the appropriate pump changes. For example, the deviceshould automatically initiate the UI process for temporary basalreduction in case b) and c) described above. Those skilled in the artwill understand that the UI may take many different forms withoutdeparting from the scope of the present invention.

Because of the acute affect of hypoglycemia, a user is likely to use theabove described process to avoid low-alarm occurrence. However, it isconceivable that a similar strategy can be used to avoid exposure to thehazards of hyperglycemia.

Not only can alarms be avoided using the various embodiments of theinvention described above, but using a combined CGM and pump device, theactual state of low glucose level, or hypoglycemia, can be avoided. Thisfurther enhances the safety and usability of such CGM devices andinsulin delivery pumps. Such an approach is also advantageous whencompared to using a CGM based projected alarm feature alone which canresult in annoying false positives and has much more limited future timeprojection. The described approach is also superior to muting an alarmto avoid the nuisance of repeated alarms and is also less annoying thana persistent projected low alarm. The user initiated, on-demand natureof the design and the pump control modification UI process integrationaffords better user control and allows more proactive user interventionto reduce glycemic variability. The embodiments of the inventiondescribed above are also advantageous because they can be used as aseparate bedtime basal analysis to adjust the basal insulin rateslightly before going to bed. Such an adjustment is especially useful ifthe user if in a carbohydrate deficient state and does not wish to eatany food before going to bed, thus giving the user the option ofreducing the basal rate of insulin delivery before going to bed.

Low glucose or hypoglycemia alarms are typically incorporated intocontinuous glucose monitoring systems to alert the user to potentiallydangerous low glucose levels. For example, the low glucose alarm in theFreestyle Navigator® Continuous Glucose Monitoring System, distributedby Abbott Diabetes Care, is sounded when a user's glucose level fallsbelow a user-defined low glucose threshold. This type of alarm may besubject to false triggering due to sensor signal anomalies such assensor drop-outs, which are temporary and fully-recoverable signalattenuations believed to be associated with the application of pressureon the percutaneous sensor and/or transmitter as may occur during sleep.

The frequency of these false low-glucose alarms may be increased duringclosed-loop insulin delivery as the control algorithm will attempt tonormalize glucose levels, increasing the percentage of time spent in ornear the euglycemic range. Sensor drop outs that occur duringhyperglycemia are less likely to trigger low glucose alarms because ofthese elevated glucose levels. In such a case, sensor drop outs may notsufficiently attenuate the sensor signal to elicit this response.However, if a user's glucose level is maintained closer to theeuglycemic (acceptable, that is, neither hypo-nor hyperglycemic) range,as is expected during close-loop control, there is an increasedlikelihood that sensor drop-out will result in signal attenuationsufficient to cross the low glucose alarm threshold, which results inthe presentation of an alarm condition to the user.

Under closed-loop conditions, where the presence of a closed-loopinsulin delivery algorithm offers the additional hazard mitigation ofthe automatic reduction or suspension of insulin delivery based uponreal-time glucose level measurements (or based upon the recent historyof glucose readings), an alternative low glucose alarm approach may bepreferred. In this embodiment, the low glucose level alarm is triggeredwhen a low glucose threshold is exceeded for a clinically significantduration.

Various embodiments of such a delayed low glucose alarm are possible.For example, the alarm may be programmed to sound:

-   -   (1) after X minutes of continuous glucose measurements had been        detected below some critical glucose value Y, where X₁=0; Y₁=40        mg/dl; where X₂=30; Y₂=45 mg/dl; and where X₃=120; Y₃=60 mg/dl;        or    -   (2) After a continuous glucose measurement had been detected        below some critical threshold A and had not recovered to either        that critical threshold A or some intermediary threshold B        within some specified duration (A′ and B′); or    -   (3) After some cumulative measure of time and duration below a        low-glucose threshold, such as when the integral of some low        glucose threshold minus the glucose profile exceeds a specified        value before the continuous glucose level measurements have        recovered to some specified value; or    -   (4) After X minutes of closed loop insulin delivery rate (or        total volume administered) below some specified threshold. In        this case, insulin delivered is treated as a surrogate for        measured glucose level due to the anticipated function of the        control algorithm programmed into the software that is operating        in the controller and/or pump.

Such an alarm approach is likely to reduce the frequency of false lowglucose alarms by allowing for the possibility of the complete orpartial recovery from the sensor-drop out to occur prior to the alarmpresentation to the user. This loosening of alarm conditions is enabledby the increased safety to the user associated with the reduced ordiscontinued insulin infusion upon low continuous glucose values that isoffered by a close-loop insulin level algorithm.

In another one embodiment of the invention, critical glucose levelvalues are used to define the time allowed before the alarm sounds,resulting in a delayed alarm. For example, the time allowed value couldbe any appropriate function of glucose level, such as, for example only,and not limited to, a linear relationship.

For example, in one embodiment, the processor re-evaluates the timeallowed before the alarm is sounded at every newly received glucoselevel measurement which is below some pre-defined or user set value.Using such an approach, if the glucose level is at 60 mg/dL (andpreviously above 60 mg/dL), then the time until the alarm sounded woulddetermined to be 60 minutes. One minute later, when the next glucoselevel value is calculated, the “time until alarm sound” may becalculated to be the lesser of 59 minutes, that is, 60 minutesdecremented by one, and the time associated with a linear function;which may be, for example, 3 minutes for every 1 mg/dL that the glucosevalue is below 60 mg/dL. Thus, if the second glucose value is 55 mg/dL,a decrease in glucose of 15 mg/dL, then the new “time until alarm sound”will be 45 minutes (60 minutes−(3 minutes per mg/dL×15 mg/dL). Thisdetermination is repeated for every glucose value received until thealarm sounds or the user's glucose level is greater than 60 mg/dL.Various approaches to this problem may be used individually or incombination in order to minimize false hypoglycemic alarms due to dropouts.

Yet another embodiment of the present invention utilizes model basedvariable risk determinations to calculate an alarm delay to prevent theannunciation of false alarms, while still providing acceptableprotection against a user entering an unacceptable glucose levelcondition. When CGM systems are used by persons with good glucosecontrol, either by fully manual means, fully automated closed loopoperation, or any hybrid means in between, the users glucose willtypically be controlled much closer to the euglycemia range than wouldotherwise occur. This close control, coupled with the expected errordistribution of CGM measurements, means that there will be an increasedlikelihood of CGM values close to or below the hypoglycemia limit. Inaddition to CGM calibration error, certain CGM signal distortionphenomena such as night time dropouts also increase the likelihood of anunderreported glucose value by the CGM system.

The combination of the three aforementioned factors interacts withstandard hypoglycemia detectors to produce a higher incidence of falsealarm rates. One embodiment of the invention designed to deal with thisproblem has been described above. Other approaches are also possible,and intended to be within the scope of the present invention, such asraising the importance and persistency of alarms depending on the lengthof time the alarm condition has existed without action by the user. Suchapproaches allow for false hypoglycemic alarms due to a combination ofthe three aforementioned factors to be minimized.

There will, however, be instances where the patient's physiology andactivity temporally pushes their glucose profile out of euglycemia andinto either a higher likelihood of hypoglycemia or hyperglycemia.Examples of events where hyperglycemia is more likely would be afterexercise, of after a meal where the user failed to receive aninsufficient prandial bolus of insulin.

If the user has a system including a CGM and an insulin delivery pump,information from the devices can be pooled or shared, and a model-basedmonitoring system can be used to modify the alarm mechanism to moreefficiently minimize false alarms without imposing unnecessary risk tothe patient. Using the information available from the CGM glucosemonitor and insulin delivery system, as well as other informationentered by the user whenever available (for example, the amount ofexercise, state of health, and the like), a model-based system definedby appropriate software commands running on a processor of a controllercan perform a prediction of glucose in terms of best estimate andupper/lower bounds for the present time up to a finite horizon in thefuture. Such a system can be achieved, for example, by implementing theuser's model in the form of a Kalman Filter framework, where both thebest estimate and variance of each model state is estimated, predicted,and modeled.

Using the present-to-near-future best estimate and bounds, the user'smost likely temporal range can be inferred. For example, assume thehypoglycemic detection mechanism of the programming of the controller orpump has 3 levels: 1) wait 30 minutes when the CGM determined glucoselevel crosses a 60 mg/dL threshold; 2) wait 15 minutes when the CGMdetermined glucose level crosses a 50 mg/dL threshold, and 3) alarmimmediately when the CGM glucose level crosses a 45 mg/dL threshold. AKalman framework may be used to determine the likelihood for a predictedfuture glucose level, given the user's current CGM glucose level andother insulin delivery history. This mechanism is implemented “as is”when the model's temporal glucose range suggests the lowest hypoglycemiclikelihood. As the likelihood reaches the middle-range risk, then themechanism is implemented with a 50% shortening of the pre-set delay forsounding the hypoglycemic alarm. For example, the detection levels setforth above may be modified as follows: 1′) wait 15 minutes when the CGMglucose level crosses the 60 mg/dL threshold; 2′) wait 7.5 minutes whenthe CGM glucose level crosses the 50 mg/dL threshold, and 3′) alarmimmediately when the CGM glucose level crosses the 45 mg/dL threshold.When the highest risk of hypoglycemic likelihood is determined, thealarm threshold has 0 delay.

In another embodiment, the same mechanism is implemented, that is: a)wait 30 minutes when the CGM glucose level crosses the 60 mg/dLthreshold; b) wait 15 minutes when the CGM glucose level crosses the 50gm/dL threshold; and 3) alarm immediately when the CGM glucose levelcrosses the 45 mg/dL threshold) when the model' temporal glucose rangesuggests the lowest hypoglycemic likelihood. In the middle-range risk,the same delays are retained, but the threshold values are increased,such as, for example: a′) wait 30 minutes when the CGM glucose levelcrosses the 60+5 mg/dL threshold; b′) wait 15 minutes when the CGMglucose level crosses the 50+5 mg/dL threshold; and c′) alarmimmediately when the CGM glucose level crosses the crosses 45+5 mg/dLthreshold.

In yet another embodiment, a hybrid of the two previous embodiments maybe used. In such an embodiment, both the threshold values and the delaytime may be adjusted based on the temporal glucose range determined bythe model.

The same types of mechanisms may be applied to hyperglycemia detection,with the tiered thresholds increasing in the order of threshold values.For example, where the CGM glucose level crosses a 180 mg/dL thresholdthe longest delay time is implemented; where the CGM glucose levelcrosses a 200 mg/dL threshold, a shorter delay time is implementedbefore sounding an alarm; and where the CGM glucose level crosses a 220gm/dL threshold, an even shorter delay time is implemented, up to amaximum threshold with a zero delay time.

While several specific embodiments of the invention have beenillustrated an described, it will be apparent that various modificationscan be made without departing from the spirit and scope of theinvention. Accordingly, it is not intended that the invention belimited, except as by the appended claims.

1. A method for determining a bolus volume to be administered to make upfor a cessation of basal delivery of insulin, comprising: determining anamount of insulin remaining in a user's body such thatinsulin remaining=amount of insulin delivered before cessation×(user'sinsulin action time minus the time since insulin was lastdelivered)/(user's insulin action time); and calculating a bolusdelivery to equal the amount of basal delivery lost.
 2. The method ofclaim 1, wherein determining an amount of insulin remaining includesusing a model to estimate the amount of insulin remaining.
 3. A methodof determining an insulin delivery rate when a closed loop insulindelivery system terminates unexpectedly, comprising: a) providing aglucose level and predicting a future glucose level in order todetermine the appropriate insulin bolus for the latest control action,and assuming that this commanded is immediately followed by open loopcontrol where the pre-programmed basal delivery amount will be in effectthereafter; b) analyzing the future glucose level using this latestbolus value plus a future basal rate to determine if the future glucoselevel is acceptable, and if so, waiting for a selected period of timeand repeating step a); c) if the glucose level of step b) is notacceptable, computing an alternate maximum temporary basal deliveryamount that is lower than the previously assumed basal rate, such thatthe predicted future glucose level is acceptable, and if so, providing atemporary basal command at the computed basal rate and duration, andpredicting a future glucose level; and if so, waiting for a selectedperiod of time and repeating step a); d) if the predicted future glucoselevel is unacceptable, projecting a future glucose level using thelowest temporary basal delivery rate computable in step c) and a maximumduration that is shorter than the maximum delivery duration, and, if thefuture glucose level is acceptable, providing a temporary basal commandincluding the rate and duration of along with a nominal bolus commandand then wait for a selected period of time and repeat step a); and f)reducing the bolus command by minimum bolus resolution and repeat stepa) such that the combination of the reduced bolus and a suitabletemporary basal rate results in an acceptable predicted glucose profileif calculating a lower alternate temporary basal rate or a lower andshorter temporary basal rate does not result in an acceptable futureglucose level.
 4. The method of claim 3, further comprising alerting theuser to take action to counter the effect of excessive insulin if anacceptable glucose profile cannot be obtained in step f) above.
 5. Amethod for predicting insulin needs at a future time to avoid unwantedout of range alarms and adjusting current insulin delivery; comprising:providing a current glucose level; providing a future time when apredicted glucose level is required; determining the predicted level atthe future time based upon the current glucose level, a value forinsulin on board, current bolus parameters and current parametersdefining an acceptable range of glucose levels; and adjusting insulindelivery to maintain the glucose level in a target range.
 6. A methodfor reducing false hypoglycemic alarms in a system under closed loopcontrol; comprising: a) providing a current glucose level; b)determining if the first level is below a threshold level and if so,providing a further glucose level at the expiration of a selected periodof time; c) determining if the glucose level taken after the expirationof the selected period of time is below the threshold level, and if so,alerting the user of a low glucose condition if the time betweenproviding the two glucose levels is greater than a selected duration oftime, and if not, repeating step c) until either the time since thecurrent glucose level and the last further glucose level exceeds theselected duration of time or the last further glucose level is above thethreshold level.
 7. A method of adjusting glucose level alarm thresholdsand alarm enunciation delay times in a system using CGM and insulindelivery system information, comprising: using a model based stateestimation, determining a predicted future glucose level and alert auser only if the predicted future glucose level falls outside of apredetermined acceptable range.
 8. The method of claim 7, wherein themodel based state estimation is a Kalman filter.
 9. The method of claim7, wherein the model based state estimation assesses the likelihood thata CGM measurement that exceeds a high or low threshold is due to a trueevent.
 10. The method of claim 7, wherein the model based stateestimation assesses the likelihood that a CGM measurement that exceeds ahigh or low threshold is due to a sensor artifact.
 11. The method ofclaim 9, wherein the likelihood is determined by comparing thedifference between the latest CGM measurement and interstitial glucosecomputed by the model prior to the latest CGM measurement.
 12. Themethod of claim 11, further comprising adjusting the glucose alarmenunciation by adjusting the threshold level and duration in which theCGM measurement exceeds a given threshold before an alarm is enunciated.13. The method of claim 12, wherein a decreasing CGM signal close to alow threshold alarm value that is not accompanied by a correspondingamount of insulin history will result in a low threshold alarm beingmade less sensitive by lowering the threshold value and/or increasingthe duration of delay before the CGM signal results in enunciation of alow threshold alarm.
 14. The method of claim 12, wherein a decreasingCGM signal close to a low threshold alarm value that is accompanied byan insulin history that should have generated a much lower CGM valuethan is measured results in a low threshold alarm being made moresensitive by increasing the threshold value and/or decreasing theduration of delay before the CGM signal results in the enunciation of alow threshold alarm.
 15. The method of claim 12, wherein an increasingCGM signal close to a high threshold alarm value that is not accompaniedby an appreciable amount of insulin history results in a high thresholdalarm being made more sensitive by lowering the threshold value and/ordecreasing the duration of delay before the CGM signal results in theenunciation of a high threshold alarm.
 16. The method of claim 12,wherein an increasing CGM signal close to a high threshold alarm valuethat is accompanied by an appreciable amount of insulin history resultsin a high threshold alarm being made less sensitive by increasing thethreshold value and/or increasing the duration of delay before the CGMsignal results in the enunciation of a high threshold alarm.
 17. Amethod of determining a latest insulin delivery amount and a temporaryinsulin delivery rate to be delivered when a closed loop insulindelivery system terminates unexpectedly, comprising: a) providing aglucose level and predicting a future glucose level in order todetermine the appropriate insulin amount for the latest control action,and assuming that this commanded is immediately followed by open loopcontrol where the pre-programmed temporary basal rate will be in effectthereafter; b) analyzing the future glucose level using this latestinsulin amount plus a future temporary basal rate to determine if thefuture glucose level is acceptable, and if so, waiting for a selectedperiod of time and repeating step a); c) if the glucose level of step b)is not acceptable, computing an alternate maximum temporary basaldelivery amount that is lower than the previously assumed basal rate,such that the predicted future glucose level is acceptable, and if so,providing a temporary basal command at the computed basal rate andduration, and predicting a future glucose level; and if so, waiting fora selected period of time and repeating step a); d) if the predictedfuture glucose level is unacceptable, projecting a future glucose levelusing the lowest temporary basal delivery rate computable in step c) anda maximum duration that is shorter than the maximum delivery duration,and, if the future glucose level is acceptable, providing a temporarybasal command including the rate and duration of along with a nominallatest insulin delivery command and then wait for a selected period oftime and repeat step a); and f) reducing the latest insulin deliverycommand by a predetermined minimum insulin delivery resolution andrepeat step a) such that the combination of the reduced latest insulindelivery amount and a suitable temporary basal rate results in anacceptable predicted glucose profile if calculating a lower alternatetemporary basal rate or a lower and shorter temporary basal rate doesnot result in an acceptable future glucose level.